Overview

Dataset statistics

Number of variables9
Number of observations338
Missing cells100
Missing cells (%)3.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory24.6 KiB
Average record size in memory74.4 B

Variable types

Text4
DateTime3
Numeric2

Dataset

Description아파트 현황
Author경기도 화성시
URLhttps://www.data.go.kr/data/3044386/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
동수 has 76 (22.5%) missing valuesMissing
관리사무소 전화번호 has 20 (5.9%) missing valuesMissing
소재지주소 has unique valuesUnique

Reproduction

Analysis started2023-12-11 23:58:29.580878
Analysis finished2023-12-11 23:58:30.639448
Duration1.06 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

아파트명
Text

Distinct332
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2023-12-12T08:58:30.781252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length22
Mean length12.863905
Min length4

Characters and Unicode

Total characters4348
Distinct characters304
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique327 ?
Unique (%)96.7%

Sample

1st row동심주택(국민주택)
2nd row시라맨숀
3rd row태안연립주택(국민주택)
4th row삼괴아파트(국민주택)
5th row우정아파트
ValueCountFrequency (%)
동탄 39
 
5.9%
아파트 16
 
2.4%
향남시범 15
 
2.3%
1단지 11
 
1.7%
2단지 11
 
1.7%
동탄시범 11
 
1.7%
반도유보라 11
 
1.7%
사랑으로 8
 
1.2%
봉담 8
 
1.2%
동탄역 8
 
1.2%
Other values (408) 527
79.2%
2023-12-12T08:58:31.097118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
327
 
7.5%
아 169
 
3.9%
파 161
 
3.7%
트 153
 
3.5%
동 136
 
3.1%
을 123
 
2.8%
마 123
 
2.8%
지 106
 
2.4%
탄 90
 
2.1%
단 82
 
1.9%
Other values (294) 2878
66.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3548
81.6%
Space Separator 327
 
7.5%
Decimal Number 261
 
6.0%
Close Punctuation 75
 
1.7%
Open Punctuation 75
 
1.7%
Uppercase Letter 26
 
0.6%
Other Punctuation 10
 
0.2%
Math Symbol 8
 
0.2%
Dash Punctuation 8
 
0.2%
Lowercase Letter 6
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 169
 
4.8%
파 161
 
4.5%
트 153
 
4.3%
동 136
 
3.8%
을 123
 
3.5%
마 123
 
3.5%
지 106
 
3.0%
탄 90
 
2.5%
단 82
 
2.3%
시 71
 
2.0%
Other values (266) 2334
65.8%
Decimal Number
ValueCountFrequency (%)
2 69
26.4%
1 69
26.4%
0 25
 
9.6%
3 23
 
8.8%
7 17
 
6.5%
5 14
 
5.4%
8 12
 
4.6%
6 12
 
4.6%
4 11
 
4.2%
9 9
 
3.4%
Uppercase Letter
ValueCountFrequency (%)
L 8
30.8%
H 8
30.8%
C 3
 
11.5%
K 2
 
7.7%
S 2
 
7.7%
A 2
 
7.7%
G 1
 
3.8%
Lowercase Letter
ValueCountFrequency (%)
c 2
33.3%
k 2
33.3%
e 1
16.7%
s 1
16.7%
Space Separator
ValueCountFrequency (%)
327
100.0%
Close Punctuation
ValueCountFrequency (%)
) 75
100.0%
Open Punctuation
ValueCountFrequency (%)
( 75
100.0%
Other Punctuation
ValueCountFrequency (%)
. 10
100.0%
Math Symbol
ValueCountFrequency (%)
~ 8
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3552
81.7%
Common 764
 
17.6%
Latin 32
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 169
 
4.8%
파 161
 
4.5%
트 153
 
4.3%
동 136
 
3.8%
을 123
 
3.5%
마 123
 
3.5%
지 106
 
3.0%
탄 90
 
2.5%
단 82
 
2.3%
시 71
 
2.0%
Other values (267) 2338
65.8%
Common
ValueCountFrequency (%)
327
42.8%
) 75
 
9.8%
( 75
 
9.8%
2 69
 
9.0%
1 69
 
9.0%
0 25
 
3.3%
3 23
 
3.0%
7 17
 
2.2%
5 14
 
1.8%
8 12
 
1.6%
Other values (6) 58
 
7.6%
Latin
ValueCountFrequency (%)
L 8
25.0%
H 8
25.0%
C 3
 
9.4%
K 2
 
6.2%
c 2
 
6.2%
S 2
 
6.2%
A 2
 
6.2%
k 2
 
6.2%
e 1
 
3.1%
s 1
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3548
81.6%
ASCII 796
 
18.3%
None 4
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
327
41.1%
) 75
 
9.4%
( 75
 
9.4%
2 69
 
8.7%
1 69
 
8.7%
0 25
 
3.1%
3 23
 
2.9%
7 17
 
2.1%
5 14
 
1.8%
8 12
 
1.5%
Other values (17) 90
 
11.3%
Hangul
ValueCountFrequency (%)
아 169
 
4.8%
파 161
 
4.5%
트 153
 
4.3%
동 136
 
3.8%
을 123
 
3.5%
마 123
 
3.5%
지 106
 
3.0%
탄 90
 
2.5%
단 82
 
2.3%
시 71
 
2.0%
Other values (266) 2334
65.8%
None
ValueCountFrequency (%)
㈜ 4
100.0%

소재지주소
Text

UNIQUE 

Distinct338
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2023-12-12T08:58:31.321503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length27
Mean length21.544379
Min length15

Characters and Unicode

Total characters7282
Distinct characters150
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique338 ?
Unique (%)100.0%

Sample

1st row경기도 화성시 향남읍 도이1길 49
2nd row경기도 화성시 봉담읍 참샘길 26
3rd row경기도 화성시 진안동 병점로23-5 (관리소)
4th row경기도 화성시 우정읍 조암로 52-5 (가동)
5th row경기도 화성시 우정읍 조암서로22번길 7-3
ValueCountFrequency (%)
경기도 338
20.2%
화성시 338
20.2%
향남읍 38
 
2.3%
봉담읍 37
 
2.2%
반송동 34
 
2.0%
병점동 28
 
1.7%
능동 21
 
1.3%
남양읍 18
 
1.1%
청계동 18
 
1.1%
오산동 17
 
1.0%
Other values (415) 787
47.0%
2023-12-12T08:58:31.707809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1342
18.4%
동 378
 
5.2%
기 358
 
4.9%
시 357
 
4.9%
화 354
 
4.9%
성 353
 
4.8%
도 341
 
4.7%
경 340
 
4.7%
로 308
 
4.2%
1 245
 
3.4%
Other values (140) 2906
39.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4660
64.0%
Space Separator 1342
 
18.4%
Decimal Number 1189
 
16.3%
Dash Punctuation 73
 
1.0%
Close Punctuation 8
 
0.1%
Open Punctuation 8
 
0.1%
Other Punctuation 1
 
< 0.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 378
 
8.1%
기 358
 
7.7%
시 357
 
7.7%
화 354
 
7.6%
성 353
 
7.6%
도 341
 
7.3%
경 340
 
7.3%
로 308
 
6.6%
길 150
 
3.2%
탄 128
 
2.7%
Other values (124) 1593
34.2%
Decimal Number
ValueCountFrequency (%)
1 245
20.6%
2 204
17.2%
3 129
10.8%
5 114
9.6%
4 97
 
8.2%
0 90
 
7.6%
6 86
 
7.2%
7 82
 
6.9%
9 81
 
6.8%
8 61
 
5.1%
Space Separator
ValueCountFrequency (%)
1342
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 73
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4660
64.0%
Common 2621
36.0%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 378
 
8.1%
기 358
 
7.7%
시 357
 
7.7%
화 354
 
7.6%
성 353
 
7.6%
도 341
 
7.3%
경 340
 
7.3%
로 308
 
6.6%
길 150
 
3.2%
탄 128
 
2.7%
Other values (124) 1593
34.2%
Common
ValueCountFrequency (%)
1342
51.2%
1 245
 
9.3%
2 204
 
7.8%
3 129
 
4.9%
5 114
 
4.3%
4 97
 
3.7%
0 90
 
3.4%
6 86
 
3.3%
7 82
 
3.1%
9 81
 
3.1%
Other values (5) 151
 
5.8%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4660
64.0%
ASCII 2622
36.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1342
51.2%
1 245
 
9.3%
2 204
 
7.8%
3 129
 
4.9%
5 114
 
4.3%
4 97
 
3.7%
0 90
 
3.4%
6 86
 
3.3%
7 82
 
3.1%
9 81
 
3.1%
Other values (6) 152
 
5.8%
Hangul
ValueCountFrequency (%)
동 378
 
8.1%
기 358
 
7.7%
시 357
 
7.7%
화 354
 
7.6%
성 353
 
7.6%
도 341
 
7.3%
경 340
 
7.3%
로 308
 
6.6%
길 150
 
3.2%
탄 128
 
2.7%
Other values (124) 1593
34.2%

승인일
Date

Distinct244
Distinct (%)72.4%
Missing1
Missing (%)0.3%
Memory size2.8 KiB
Minimum1983-01-01 00:00:00
Maximum2017-11-29 00:00:00
2023-12-12T08:58:31.835405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:58:31.960497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

준공일
Date

Distinct286
Distinct (%)84.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
Minimum1984-11-21 00:00:00
Maximum2019-09-30 00:00:00
2023-12-12T08:58:32.084809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:58:32.220963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

층수
Text

Distinct128
Distinct (%)38.2%
Missing3
Missing (%)0.9%
Memory size2.8 KiB
2023-12-12T08:58:32.476004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length3.1701493
Min length1

Characters and Unicode

Total characters1062
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique70 ?
Unique (%)20.9%

Sample

1st row3
2nd row3
3rd row3
4th row3
5th row4
ValueCountFrequency (%)
15 40
 
11.9%
20 23
 
6.9%
25 22
 
6.6%
4 11
 
3.3%
3 10
 
3.0%
29 9
 
2.7%
18 8
 
2.4%
18~20 7
 
2.1%
12~15 6
 
1.8%
5 6
 
1.8%
Other values (118) 193
57.6%
2023-12-12T08:58:32.838105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 247
23.3%
2 193
18.2%
~ 148
13.9%
5 130
12.2%
0 86
 
8.1%
3 80
 
7.5%
8 50
 
4.7%
4 43
 
4.0%
9 27
 
2.5%
6 26
 
2.4%
Other values (3) 32
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 907
85.4%
Math Symbol 148
 
13.9%
Uppercase Letter 5
 
0.5%
Space Separator 2
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 247
27.2%
2 193
21.3%
5 130
14.3%
0 86
 
9.5%
3 80
 
8.8%
8 50
 
5.5%
4 43
 
4.7%
9 27
 
3.0%
6 26
 
2.9%
7 25
 
2.8%
Math Symbol
ValueCountFrequency (%)
~ 148
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 5
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1057
99.5%
Latin 5
 
0.5%

Most frequent character per script

Common
ValueCountFrequency (%)
1 247
23.4%
2 193
18.3%
~ 148
14.0%
5 130
12.3%
0 86
 
8.1%
3 80
 
7.6%
8 50
 
4.7%
4 43
 
4.1%
9 27
 
2.6%
6 26
 
2.5%
Other values (2) 27
 
2.6%
Latin
ValueCountFrequency (%)
B 5
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1062
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 247
23.3%
2 193
18.2%
~ 148
13.9%
5 130
12.2%
0 86
 
8.1%
3 80
 
7.5%
8 50
 
4.7%
4 43
 
4.0%
9 27
 
2.5%
6 26
 
2.4%
Other values (3) 32
 
3.0%

동수
Real number (ℝ)

MISSING 

Distinct20
Distinct (%)7.6%
Missing76
Missing (%)22.5%
Infinite0
Infinite (%)0.0%
Mean4.648855
Minimum1
Maximum24
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2023-12-12T08:58:32.943909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q38
95-th percentile13.95
Maximum24
Range23
Interquartile range (IQR)7

Descriptive statistics

Standard deviation4.7179833
Coefficient of variation (CV)1.01487
Kurtosis0.68022182
Mean4.648855
Median Absolute Deviation (MAD)1
Skewness1.1864163
Sum1218
Variance22.259366
MonotonicityNot monotonic
2023-12-12T08:58:33.046296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
1 121
35.8%
2 23
 
6.8%
9 22
 
6.5%
3 12
 
3.6%
7 11
 
3.3%
13 11
 
3.3%
8 10
 
3.0%
6 9
 
2.7%
5 8
 
2.4%
11 6
 
1.8%
Other values (10) 29
 
8.6%
(Missing) 76
22.5%
ValueCountFrequency (%)
1 121
35.8%
2 23
 
6.8%
3 12
 
3.6%
4 5
 
1.5%
5 8
 
2.4%
6 9
 
2.7%
7 11
 
3.3%
8 10
 
3.0%
9 22
 
6.5%
10 5
 
1.5%
ValueCountFrequency (%)
24 1
 
0.3%
19 1
 
0.3%
18 1
 
0.3%
17 2
 
0.6%
16 2
 
0.6%
15 2
 
0.6%
14 5
1.5%
13 11
3.3%
12 5
1.5%
11 6
1.8%

세대수
Real number (ℝ)

Distinct282
Distinct (%)83.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean626.56805
Minimum12
Maximum2342
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2023-12-12T08:58:33.155360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum12
5-th percentile46.55
Q1362
median608
Q3840.5
95-th percentile1318.1
Maximum2342
Range2330
Interquartile range (IQR)478.5

Descriptive statistics

Standard deviation392.54869
Coefficient of variation (CV)0.62650609
Kurtosis1.4314837
Mean626.56805
Median Absolute Deviation (MAD)245
Skewness0.8386263
Sum211780
Variance154094.48
MonotonicityNot monotonic
2023-12-12T08:58:33.280339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
90 5
 
1.5%
40 4
 
1.2%
617 3
 
0.9%
514 3
 
0.9%
470 3
 
0.9%
649 3
 
0.9%
622 3
 
0.9%
915 2
 
0.6%
534 2
 
0.6%
700 2
 
0.6%
Other values (272) 308
91.1%
ValueCountFrequency (%)
12 1
 
0.3%
15 1
 
0.3%
16 2
0.6%
18 1
 
0.3%
21 2
0.6%
30 1
 
0.3%
34 1
 
0.3%
36 2
0.6%
39 1
 
0.3%
40 4
1.2%
ValueCountFrequency (%)
2342 1
0.3%
2147 1
0.3%
1967 1
0.3%
1817 1
0.3%
1742 1
0.3%
1552 1
0.3%
1538 1
0.3%
1526 1
0.3%
1515 1
0.3%
1499 1
0.3%

관리사무소 전화번호
Text

MISSING 

Distinct310
Distinct (%)97.5%
Missing20
Missing (%)5.9%
Memory size2.8 KiB
2023-12-12T08:58:33.524920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.144654
Min length11

Characters and Unicode

Total characters3862
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique302 ?
Unique (%)95.0%

Sample

1st row031-222-7767
2nd row031-358-4049
3rd row031-352-6396
4th row031-357-9263
5th row031-352-4543
ValueCountFrequency (%)
031-613-7042 2
 
0.6%
031-358-3110 2
 
0.6%
031-8015-2222 2
 
0.6%
031-231-9659 2
 
0.6%
031-377-9081 2
 
0.6%
031-225-9165 2
 
0.6%
031-372-2767 2
 
0.6%
031-237-5114 2
 
0.6%
031-8059-6027 1
 
0.3%
031-8003-7043 1
 
0.3%
Other values (300) 300
94.3%
2023-12-12T08:58:33.906904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 698
18.1%
- 636
16.5%
0 549
14.2%
1 512
13.3%
2 293
7.6%
7 248
 
6.4%
5 241
 
6.2%
8 223
 
5.8%
6 193
 
5.0%
4 144
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3226
83.5%
Dash Punctuation 636
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 698
21.6%
0 549
17.0%
1 512
15.9%
2 293
9.1%
7 248
 
7.7%
5 241
 
7.5%
8 223
 
6.9%
6 193
 
6.0%
4 144
 
4.5%
9 125
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 636
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3862
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 698
18.1%
- 636
16.5%
0 549
14.2%
1 512
13.3%
2 293
7.6%
7 248
 
6.4%
5 241
 
6.2%
8 223
 
5.8%
6 193
 
5.0%
4 144
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3862
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 698
18.1%
- 636
16.5%
0 549
14.2%
1 512
13.3%
2 293
7.6%
7 248
 
6.4%
5 241
 
6.2%
8 223
 
5.8%
6 193
 
5.0%
4 144
 
3.7%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
Minimum2019-11-14 00:00:00
Maximum2019-11-14 00:00:00
2023-12-12T08:58:34.011655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:58:34.096530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T08:58:30.163651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:58:29.991329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:58:30.249142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:58:30.082196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T08:58:34.155730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
동수세대수
동수1.0000.553
세대수0.5531.000
2023-12-12T08:58:34.222933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
동수세대수
동수1.0000.295
세대수0.2951.000

Missing values

2023-12-12T08:58:30.368764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T08:58:30.485887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-12-12T08:58:30.579955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

아파트명소재지주소승인일준공일층수동수세대수관리사무소 전화번호데이터기준일자
0동심주택(국민주택)경기도 화성시 향남읍 도이1길 491983-01-011984-11-213<NA>21<NA>2019-11-14
1시라맨숀경기도 화성시 봉담읍 참샘길 261984-04-191984-12-013190031-222-77672019-11-14
2태안연립주택(국민주택)경기도 화성시 진안동 병점로23-5 (관리소)1984-08-041985-12-113<NA>54<NA>2019-11-14
3삼괴아파트(국민주택)경기도 화성시 우정읍 조암로 52-5 (가동)1985-05-171985-12-283<NA>39031-358-40492019-11-14
4우정아파트경기도 화성시 우정읍 조암서로22번길 7-31984-01-011986-04-104<NA>40<NA>2019-11-14
5삼미아파트경기도 화성시 매송면 매송고색로422번길 73 (가동)1984-01-011986-04-121~55165<NA>2019-11-14
6민성주택(국민주택)경기도 화성시 남양읍 남양시장로 65번길 191985-01-011986-05-153<NA>18<NA>2019-11-14
7천보주택(국민주택)경기도 화성시 봉담읍 진등2길 20-24 (가동)1985-05-211986-05-274<NA>40<NA>2019-11-14
8병점국민주택(국민주택)경기도 화성시 진안동 병점로 23-6 (가동)1985-05-301986-07-154172<NA>2019-11-14
9대성아파트경기도 화성시 향남읍 푸른들판로257번길 431985-10-191986-09-133<NA>40031-352-63962019-11-14
아파트명소재지주소승인일준공일층수동수세대수관리사무소 전화번호데이터기준일자
328남양 시티프라디움3차경기도 화성시 남양읍 남양천로 172015-05-062019-06-042110438031-356-42222019-11-14
329세영리첼 에듀파크경기도 화성시 새솔동 수노을중앙로 2572015-12-102019-07-30204533031-355-87452019-11-14
330송산신도시 대방노블랜드 리버스위트 2차경기도 화성시 새솔동 수노을1로 1072016-10-202019-08-122011426031-365-31682019-11-14
331송산신도시 대방노블랜드 더 센트럴 3차경기도 화성시 새솔동 수노을1로 1082016-10-202019-08-162514872031-365-32782019-11-14
332동탄호수공원아이파크경기도 화성시 장지동 동탄순환대로8길 142016-12-232019-07-302916774031-374-95102019-11-14
333중흥에스클래스더테라스리버파크1차경기도 화성시 오산동 동탄기흥로353번길 762017-07-102019-07-2944158031-8055-08642019-11-14
334중흥에스클래스더테라스리버파크2차경기도 화성시 오산동 855-12017-07-102019-07-2944104<NA>2019-11-14
335중흥에스클래스더테라스리버파크3차경기도 화성시 오산동 906-22017-07-102019-07-2944104<NA>2019-11-14
336금강펜테리움센트럴파크송산경기도 화성시 새솔동 수노을1로 1922015-09-192019-09-302014692031-357-28412019-11-14
337중흥에스클래스더테라스경기도 화성시 영천동 동탄대로24길 742017-07-102019-09-3045162031-378-25752019-11-14